Augmented reality safety

ABSTRACT

Embodiments of the present disclosure relate to augmented reality (AR) safety enhancement. In embodiments, an eye-gaze time indicating a period in which a user using an AR application is viewing a screen of a mobile device running the AR application can be determined. The eye-gaze time can then be compared to an eye-gaze threshold. In response to a determination that the eye-gaze time exceeds the eye-gaze threshold, an alert can be issued to the mobile device running the AR application. In embodiments, a set of proximity data can be received. The set of proximity data can be analyzed to determine a number of nearby devices. A determination can be made whether the number of nearby devices exceeds a safety threshold. When a determination is made that the number of nearby devices exceeds the safety threshold, an alert can be issued to a device having a running AR application.

BACKGROUND

The present disclosure relates generally to the field of augmentedreality, and in particular to augmented reality safety.

Augmented reality (AR) mobile applications leverage sensor data toemulate augmented environments. For example, an AR mobile applicationcan utilize global positioning system (GPS) technology, cameras,gyroscopes, accelerometers, etc. to augment a virtual environment withinthe application. The augmented environment can include virtualdestinations and/or objects, which can be displayed to a user via ageographic map and/or through a camera view.

SUMMARY

Embodiments of the present disclosure include a method, computer programproduct, and system for enhancing the safety within an augmented reality(AR) environment. In embodiments, an eye-gaze time indicating a periodin which a user using an AR application is viewing a screen of a mobiledevice running the AR application can be determined. The eye-gaze timecan then be compared to an eye-gaze threshold. In response to adetermination that the eye-gaze time exceeds the eye-gaze threshold, analert can be issued to the mobile device running the AR application.

In embodiments, a set of proximity data can be received. The set ofproximity data can be analyzed to determine a first number of nearbydevices. A determination can be made whether the first number of nearbydevices exceeds a first safety threshold. When a determination is madethat the first number of nearby devices exceeds the safety threshold, analert can be issued to a device having a running AR application.

In embodiments, a user position of a user using a mobile device having arunning AR application can be received. Further, a sought destinationposition for at least one virtual destination can be received. The userposition can be compared to the sought destination position at a firsttime to determine a first distance between the user position and thesought destination. When the distance satisfies a proximity threshold,an alert can be issued to the mobile device having the running ARapplication.

The above summary is not intended to describe each illustratedembodiment or every implementation of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings included in the present disclosure are incorporated into,and form part of, the specification. They illustrate embodiments of thepresent disclosure and, along with the description, serve to explain theprinciples of the disclosure. The drawings are only illustrative oftypical embodiments and do not limit the disclosure.

FIG. 1 depicts a block diagram of an example computing environment inwhich illustrative embodiments of the present disclosure may beimplemented.

FIG. 2 depicts of a block diagram of a mobile device having an augmentedreality safety overlay, in accordance with embodiments of the presentdisclosure.

FIG. 3 illustrates a flow diagram of an example method for enhancingsafety of an AR application by using eye-tracking, in accordance withembodiments of the present disclosure.

FIG. 4 illustrates a flow diagram of an example method for enhancingsafety of an AR application by using proximity detection, in accordancewith embodiments of the present disclosure.

FIG. 5 illustrates a flow diagram of an example method for enhancingsafety of an AR application by using position comparison, in accordancewith embodiments of the present disclosure.

FIG. 6 illustrates a flow diagram of an example method for classifyinglocations at particular time periods based on input safety data, inaccordance with embodiments of the present disclosure.

FIG. 7 is a high-level block diagram illustrating an example computersystem that can be used in implementing one or more of the methods,tools, and modules, and any related functions described herein, inaccordance with embodiments of the present disclosure.

FIG. 8 is a diagram illustrating a cloud computing environment, inaccordance with embodiments of the present disclosure.

FIG. 9 is a block diagram illustrating abstraction model layers, inaccordance with embodiments of the present disclosure.

While the embodiments described herein are amenable to variousmodifications and alternative forms, specifics thereof have been shownby way of example in the drawings and will be described in detail. Itshould be understood, however, that the particular embodiments describedare not to be taken in a limiting sense. On the contrary, the intentionis to cover all modifications, equivalents, and alternatives fallingwithin the spirit and scope of the disclosure.

DETAILED DESCRIPTION

Aspects of the present disclosure relate generally to the field ofaugmented reality, and in particular to augmented reality safety. Whilethe present disclosure is not necessarily limited to such applications,various aspects of the disclosure may be appreciated through adiscussion of various examples using this context.

Augmented reality (AR) mobile applications leverage sensor data toemulate augmented environments. For example, an AR mobile applicationcan utilize global positioning system (GPS) technology, cameras,gyroscopes, accelerometers, etc. to generate an augmented environmentwithin the application. The augmented environment can include virtualdestinations and/or objects, which can be displayed to a user via ageographic map and/or through a camera view.

When a user utilizes an AR mobile application, the user may frequentlyview their mobile device to track their location with respect to virtualobjects and/or destinations. These virtual objects and/or destinationscan be placed in various locations such as, for example, restaurants,parks, monuments, streets, churches, stores, etc. In some ARapplications, the virtual objects and/or destinations may be scatteredrandomly throughout a particular environment. To access the virtualobjects and/or destinations on the AR mobile application, the user maybe required to physically travel through the environment to a locationcorresponding to the location of the virtual objects/destinations. Uponreaching the physical location of a virtual object and/or destination,the user can interact with the virtual object and/or destination.

AR applications pose serious safety concerns for users. For example,because users are frequently viewing their mobile device to trackvirtual objects and/or destination, the users may not be aware of theirsurroundings in the real world. This is amplified when many users areimmersed in the same AR environment in a given area. Further, becausevirtual objects and/or locations can be randomly scattered throughoutthe real world, these virtual objects and/or locations can be disposedat dangerous locations (e.g., cliff sides, water bodies, busy streets,etc.).

Aspects of the present disclosure address the aforementionedcomplications via an AR safety overlay. The AR safety overlay can havevarious features to enhance safety for users using an AR application. Inembodiments, the AR safety overlay employs the use of eye-trackingtechnology. The eye-tracking technology can be configured to determinean amount of time a user is viewing their device while using an ARapplication. This can be used to warn the user when they are viewingtheir screen beyond a predetermined time period. In embodiments, the ARsafety overlay includes a proximity detector configured to determine anumber, speed, and/or trajectory of nearby devices. This can be used towarn a user if they are in a particularly dangerous area. Further, thisinformation can be used to classify locations within the AR environmentbased on safety. In embodiments, the AR safety overlay can include aposition comparator. The position comparator can be used to track auser's location (e.g., a device of the user) with respect to a soughtvirtual object and/or destination. Based on the distance between theuser's location and the sought virtual object or destination, one ormore notifications can be triggered, allowing the user to approach thevirtual object or destination without the need to continuously viewtheir device.

These improvements and/or advantages are a non-exhaustive list ofexample advantages. Embodiments of the present disclosure exist whichcan contain none, some, or all of the aforementioned advantages and/orimprovements.

Turning now to the figures, FIG. 1 depicts a block diagram of an examplecomputing environment 100 in which illustrative embodiments of thepresent disclosure can be implemented. The computing environment 100includes two client devices 102 and 112 and a server 122.

Consistent with various embodiments, the server 122 and the clientdevices 102 and 112 can be computer systems. The client devices 102 and112 and the server 122 can include one or more processors 106, 116, and126 and one or more memories 108, 118, and 128, respectively. The clientdevices 102 and 112 and the server 122 can be configured to communicatewith each other through an internal or external network interface 104,114, and 124. The network interfaces 104, 114, and 124 can, in someembodiments, be modems or network interface cards. The client devices102 and 112 and/or the server 122 can be equipped with a display ormonitor. Additionally, the client devices 102 and 112 and/or the server122 can include optional input devices (e.g., a keyboard, mouse,scanner, or other input device), and/or any commercially available orcustom software (e.g., browser software, communications software, serversoftware, AR software, positioning system software, eye-trackingsoftware, search engine and/or web crawling software, etc.). In someembodiments, the client devices 102 and 112 and/or the server 122 can beservers, desktops, laptops, or hand-held devices.

The client devices 102 and 112 and the server 122 can be distant fromeach other and communicate over a network 150. In some embodiments, theserver 122 can be a central hub from which client devices 102 and 112can establish a communication connection, such as in a client-servernetworking model. Alternatively, the server 122 and client devices 102and 112 can be configured in any other suitable networking relationship(e.g., in a peer-to-peer (P2P) configuration or using any other networktopology).

In some embodiments, the network 150 can be implemented using any numberof any suitable communications media. For example, the network 150 canbe a wide area network (WAN), a local area network (LAN), an internet,or an intranet. In certain embodiments, the client devices 102 and 112and the server 122 can be local to each other and communicate via anyappropriate local communication medium. For example, the client devices102 and 112 and the server 122 can communicate using a local areanetwork (LAN), one or more hardwire connections, a wireless link orrouter, or an intranet. In some embodiments, the client devices 102 and112 and the server 122 can be communicatively coupled using acombination of one or more networks and/or one or more localconnections. For example, the first client device 102 can be hardwiredto the server 122 (e.g., connected with an Ethernet cable) while thesecond client device 112 can communicate with the server 122 using thenetwork 150 (e.g., over the Internet).

In some embodiments, the network 150 may be implemented within a cloudcomputing environment, or using one or more cloud computing services.Consistent with various embodiments, a cloud computing environment caninclude a network-based, distributed data processing system thatprovides one or more cloud computing services. Further, a cloudcomputing environment can include many computers (e.g., hundreds orthousands of computers or more) disposed within one or more data centersand configured to share resources over the network 150.

In embodiments, the server 122 includes an augmented reality (AR)application 130. The AR application 130 can be configured to provide anaugmented environment having one or more virtual objects and/ordestinations disposed at physical locations in the real-world. In someembodiments, the AR application may be a game which enables users tointeract with virtual objects and/or locations by traveling to physicallocations corresponding to locations of the virtual objects and/ordestinations. In some embodiments, the AR application 130 can include aweb mapping service (not pictured) configured to aid users in routeplanning to physical locations in the real world.

In embodiments, the AR application 130 can be dispatched from the server122 for installation on the client devices 102 and 112. In someembodiments, the AR application 130 can be provisioned from the server122 to the client devices 102 and 112, such that installation on theclient devices 102 and 112 is not necessary.

The AR application 130 can leverage client device 102 and 112 featuresto generate an augmented environment. For example, the AR application130 can utilize geographic/location data of the client devices 102 and112 to generate one or more virtual objects and/or destinations atparticular real-world locations. As an example, one or more virtualobjects and/or destinations can be disposed on an electronic map atparticular points of interest (e.g., a restaurant, a monument, etc.),coordinates (e.g., longitudes/latitudes), addresses, etc. Further, theAR application 130 can utilize camera features of the client devices 102and 112 to display the virtual objects and/or destinations through acamera view. As another example, the AR application 130 can utilizegyroscope/accelerometer data of the client devices 102 and 112 todetermine device movement (e.g., trajectory and speed) with respect tovirtual objects and/or destinations. In some embodiments, the ARapplication 130 can utilize geographic/location data to guide routeplanning for users to physical locations.

As depicted in FIG. 1, the AR application 130 includes an augmentedreality safety overlay (ARSO) 132. In some embodiments, the ARSO 132 canbe included as a software package of the AR application 130. In someembodiments, the ARSO 132 can be installed separately from the ARapplication 130. In these embodiments, the ARSO 132 can be called (e.g.,initiated) upon execution of (e.g., launching) the AR application 130.For example, the ARSO 132 can be stored at the operating system (OS)level, and in response to a determination that an AR application (e.g.,AR application 130) is launched, the ARSO 132 can be initiated.

The ARSO 132 can be configured to enhance safety for users accessing theAR application 130 via the client devices 102 and 112. For example, theARSO 132 can be configured to collect eye-tracking data to notify userswhen they are viewing their devices beyond a predetermined period. Thiscan prevent collisions, missteps, and/or entrance into dangerous areas.As another example, the ARSO 132 can be configured to determine thenumber, speed, and/or trajectory of nearby devices. This information canbe utilized to warn a user if they are in a dangerous location (e.g., alocation within many moving vehicles or bikes, a crowded location withhigh risk of collision, etc.). The ARSO 132 can further be configured tonotify viewers when they arrive at (e.g., or approach) a particulardestination (e.g., physical or virtual), without requiring the viewer toconstantly view their device. The data collected/generated by the ARSO132 can then be analyzed to construct safety profiles for respectivelocations within the world. These features of the ARSO 132 will befurther discussed with reference to FIGS. 2-6.

While FIG. 1 illustrates a computing environment 100 with a singleserver 122 and two client devices 102 and 112, suitable computingenvironments for implementing embodiments of this disclosure can includeany number of client devices and servers. The various models, modules,systems, and components illustrated in FIG. 1 may exist, if at all,across a plurality of servers and client devices. For example, someembodiments may include two servers. The two servers may becommunicatively coupled using any suitable communications connection(e.g., using a WAN, a LAN, a wired connection, an intranet, or theInternet).

It is noted that FIG. 1 is intended to depict the representative majorcomponents of an exemplary computing environment 100. In someembodiments, however, individual components can have greater or lessercomplexity than as represented in FIG. 1, components other than or inaddition to those shown in FIG. 1 may be present, and the number, type,and configuration of such components may vary. For example, in someembodiments, the ARSO 132 is not stored within the AR application 130.In these embodiments, the ARSO 132 can be stored separately (e.g., atthe OS level, within another application, in a file, etc.) and initiatedupon launching (e.g., or separately executed by a user at any suitabletime) the AR application 130.

Referring now to FIG. 2, shown is a mobile device 200 (e.g., clientdevices 102 and 112 of FIG. 1) implementing an augmented reality safetyoverlay (ARSO) 225 (e.g., ARSO 132 of FIG. 1), in accordance withembodiments of the present disclosure. The mobile device 200 can includevarious components. For example, the mobile device 200 can includecomputer components such as a processor (e.g., a multi-core centralprocessing unit (CPU)), a storage system (e.g., a solid-state drive(SSD) or hard disk drive (HDD)), and a main memory (e.g., random accessmemory (e.g., RAM)). For simplicity, these components are not depictedin FIG. 2.

As shown in FIG. 2, the mobile device 200 includes a camera 205, apositioning system 210, a network interface controller (NIC) 215, and anaugmented reality (AR) application 220. The camera 205, positioningsystem 210, NIC 215, and AR application 220 are communicatively coupledto the ARSO 225. The ARSO 225 utilizes the data obtained from the camera205, positioning system 210, and NIC 215 to enhance the safety of the ARapplication 220.

In particular, an eye-tracker 230, a proximity detector 235, and aposition comparator 240 of the ARSO 225 use data obtained from thecamera 205, positioning system 210, and NIC 215 to enhance the safety ofthe AR application 220. A safety analyzer 245 of the ARSO 225 analyzesthe data obtained from the eye-tracker 230, proximity detector 235, andposition comparator 240 to determine whether conditions are safe and/orwhether notifying a user of the mobile device 200 is warranted. If thesafety analyzer 245 determines that the user of the mobile device 200should be notified, a command can be dispatched to a notifier 250 suchthat the user can be warned. Further, the data analyzed by the safetyanalyzer 245 can be dispatched to a safety profiler 255, which can beconfigured to associate the safety data (e.g., analyzed by the safetyanalyzer 245) with particular locations and generate safety scores(e.g., classify locations based on safety) for respective locations.

The eye-tracker 230 of the ARSO 225 can be configured to determine anamount of time a user is viewing a display (not shown) of the mobiledevice 200. To do so, the eye-tracker 230 can obtain visual data fromthe camera 205. The camera 205 can include both an outward-facing cameraand a front-facing camera. The front-facing camera may be orientedtoward a user using the mobile device 200. Thus, in some embodiments,the eye-tracker 230 can utilize data obtained from a front-facing camera(e.g., of the camera 205) to determine the amount of time a user isviewing the display.

In some embodiments, the eye-tracker 230 can utilize data obtained fromadditional sources to determine the amount of time a user is viewing thedisplay of the mobile device 200. For example, the eye-tracker 230 canutilize eye-attached tracking data (e.g., from smart contact lenses wornby a user), data from a head mounted display (HMD) (e.g., smart glasses)worn by a user, or data from another eye-tracking device (e.g., anelectric potential eye-tracker) to determine the amount of time a useris viewing the display of the mobile device 200. This data can bereceived by the eye-tracker 230 via the NIC 215.

To determine the amount of time a user is viewing the display, theeye-tracker 230 can be configured to analyze eye position/movement overtime. For example, the eye-tracker 230 can be configured to track eyeposition/movement via eye-attached tracking (e.g., devices attached tothe eye which track eye movements), optical tracking (e.g., by comparingthe position of eye features (e.g., the pupil) with respect to a frameof reference (e.g., a reflection of light off the eye), and/or electricpotential tracking (e.g., by measuring electric potential associatedwith electrodes placed around the eyes). Based on the eyeposition/movement over time, the eye-tracker 230 determines the amountof time a user is viewing the display in-real time (e.g., an eye-gazetime). For example, if the user eye position indicates that a user isviewing the screen (e.g., a location the user is determined to beviewing corresponds to the location of the mobile device 200 display),an eye-gaze timer can initiate until the user looks away from thescreen.

The safety analyzer 245 receives the eye-gaze time (e.g., the timeperiod in which the user is consecutively viewing the display of themobile device 200) from the eye-tracker 230 and determines whether aneye-gaze threshold (e.g., a threshold which defines an amount of time auser is permitted to view the display of the mobile device 200 withoutlooking away) is exceeded. For example, if an eye-gaze threshold forviewing the display of the mobile device 200 is defined as 4 seconds,and the eye-tracker 230 data indicates that a user has been viewing thedisplay of the mobile device 200 for 3 seconds, a determination can bemade that the eye-gaze threshold is not exceeded. However, if theeye-tracker data indicates that a user is viewing the display of themobile device 200 for 5 seconds, a determination can be made that theeye-gaze threshold is exceeded. If the safety analyzer 245 determinesthat the eye-gaze threshold is exceeded, the safety analyzer 245 candispatch a command to the notifier 250 to warn the user viewing themobile device 200. Further, the breach in the eye-gaze threshold can bestored and used later by the safety profiler 255 for classifyingrespective locations based on safety.

By ensuring that a user is not viewing the screen for a prolongedconsecutive period, the safety of the use of the AR application 220 canbe enhanced. For example, ensuring a user looks up at least every “X”seconds (e.g., based on an eye-gaze threshold) can prevent collisions,missteps, or entrance into dangerous territories (e.g., a busy street, acliff side, etc.). Eye-tracking techniques will be further discussedwith reference to FIG. 3.

The proximity detector 235 can be configured to determine the number,speed, and/or trajectory of devices in the vicinity of the mobile device200. In some embodiments, the proximity detector 235 can be configuredto determine the number, speed, and/or trajectory of devices using datareceived via the NIC 215. For example, the NIC 215 may receive data fromone or more applications (e.g., a map application, a social networkingapplication, AR application 220, etc.) which track the location of userdevices (e.g., to measure traffic, to identify nearby friends, etc.)using positioning technology. These applications may acquire GPScoordinates for respective devices, which can be updated over time. TheGPS data from these applications can be collected by the proximitydetector 235 to determine the number, speed, and/or trajectory of nearbydevices. For example, the number of devices within a given radius (e.g.,10 feet, 50 feet, 100 feet, 1 mile, etc.) of the mobile device 200(based on the acquired GPS data) can be used to determine a number ofdevices in the nearby vicinity. Further, the location of the respectivedevices over time can be measured to determine the speed of theserespective devices. By measuring the time period between two GPSmeasurements for a given device, the speed and trajectory of the devicecan be approximated.

In some embodiments, the proximity detector 235 can determine thenumber, speed, and/or trajectory of nearby devices using wirelesspositioning technology. These technologies include, but are not limitedto Wi-Fi, Bluetooth Low Energy (BLE), Radio-frequency Identification(RFID), and Ultra-wideband (UWB). Signals (e.g., the speed, strength,and/or angle of signals) traveling between transmitters (e.g., a firstmobile device) and receivers (e.g., a second mobile device) can be usedto approximate location. For example, Time of Arrival (TOA), ReceivedSignal Strength Indicator (RSSI), and/or Angle of Arrival (AOA) analysescan be used to approximate the position of a device communicating withthe mobile device 200. By measuring the location of the nearby deviceswith respect to the mobile device over time, the speed of nearby devicescan be calculated (e.g., by measuring the time period between twomeasured locations).

The number, trajectory, and/or speed of nearby devices are thendispatched to the safety analyzer 245. The safety analyzer 245 can thenuse this data to determine whether a notification is warranted by thenotifier 250. For example, the safety analyzer 245 may set one or moresafety thresholds defining conditions in which notifications should betriggered. These safety thresholds can be based on the number of deviceswithin the vicinity (e.g., if the number of devices exceeds a threshold,a notification is transmitted), the speed of devices within the vicinity(e.g., if any device exceeds a speed threshold, a notification istransmitted), the trajectory of nearby devices (e.g., whether twodevices are likely to cross paths), etc.

Additionally, the safety analyzer 245 can transmit the number, speed,and/or trajectory of devices in the vicinity of the mobile device 200 tothe safety profiler 255. The safety profiler 255 can utilize thisinformation to classify locations based on safety considerations. Forexample, a location with many high-speed devices can be classified as“dangerous” while a location with few low-speed devices can beclassified as “safe.” Classification techniques for locations will befurther discussed with reference to FIG. 6.

By considering the number, speed, and/or trajectory of nearby devices,the safety of the augmented environment can be enhanced. For example, byissuing notifications based on the number, speed, and/or trajectory ofdevices, users can quickly become aware of their surroundings whileusing the augmented reality application 220. This can allow users tocontinuously receive updates regarding the safety of new areas theyenter. Further, by profiling locations based on the historic number,speed, and/or trajectory of devices which enter these areas, users canmake informed decisions on where to travel in the future while using theAR application 220. The techniques of the proximity detector 235 will befurther discussed with reference to FIG. 4.

The position comparator 240 can be configured to compare the location ofthe mobile device 200 to the position of one or more sought destinations(e.g., physical locations and/or locations of virtualobjects/destinations) associated with the AR application 220. To do so,the position comparator 240 receives mobile device 200 location datafrom the positioning system 210 and compares the mobile device 200position to positions of sought destinations indicated on an AR map ofthe AR application 220. This can be used to provide notifications tousers attempting to arrive at particular virtual objects/destinations.

The safety analyzer 245 receives the position comparison data from theposition comparator and determines whether a notification should beissued by the notifier 250. This determination can be based on one ormore thresholds. For example, a notification can be triggered based on apredetermined distance between the mobile device 200 and a virtualdestination. By notifying the user of the mobile device 200 as theyapproach virtual objects/destinations, the amount of time the user hasto view a display of the mobile device 200 is decreased. Positioncomparison techniques will be further discussed with reference to FIG.5.

It is noted that in some embodiments the functions of the eye-tracker230, proximity detector 235, position comparator 240, safety analyzer245, notifier 250, and safety profiler 255 can be processor executableinstructions that can be executed by a dedicated or shared processorusing received input (e.g., from the camera 205, positioning system 210,NIC 215, and/or AR Application 220).

FIG. 3 is a flow diagram illustrating an example method 300 forenhancing safety of an AR application (e.g., AR application 130 of FIG.1 or 220 of FIG. 2) using eye-tracking, in accordance with embodimentsof the present disclosure.

Method 300 initiates at operation 305, where eye-tracking data isreceived (e.g., by mobile device 200 of FIG. 2). The eye-tracking datacan be received from any suitable source. For example, the eye-trackingdata can be received from a camera on a mobile device where the ARapplication is installed. In some embodiments, the eye-tracking data canbe received over a network. For example, the eye-tracking data can bereceived from eye-attached tracking devices (e.g., smart contactlenses), a head mounted display (e.g., smart glasses), or aneye-tracking device (e.g., an electric potential eye-tracking device).In embodiments, the eye-tracking data can be produced via eye-trackingsoftware. The eye-tracking software may perform eye-tracking analysisbased on eye-attached tracking, optical eye-tracking, and/or electricpotential eye-tracking. The eye-tracking analysis may include thelocations (e.g., coordinates) where a user's eyes are looking over time.

An eye-gaze time is then determined. This is illustrated at operation310. The eye-gaze time can be determined based on the number ofconsecutive seconds a user has been viewing a display (e.g., a screen)of their device (e.g., as indicated in the eye-tracking data received atoperation 305). For example, if the eye-tracking data received atoperation 305 indicates that a user has been viewing their screen for 10consecutive seconds, the eye-gaze time would be determined to be 10seconds.

A determination is then made whether an eye-gaze threshold is exceeded.This is illustrated at operation 315. The eye-gaze threshold defines thepermitted screen eye-gaze time. The eye-gaze threshold can be defined inany suitable manner.

In some embodiments, the eye-gaze threshold can be set to a fixed value(e.g., manually by a user). For example, assuming an eye-gaze thresholdis set to 10 seconds, if a screen eye-gaze time is determined to be 11seconds, then a determination is made that the eye-gaze threshold isexceeded.

In some embodiments, the eye-gaze threshold is dynamicallydetermined/adjusted. In some embodiments, the eye-gaze threshold can bedetermined based on surrounding geographic data (e.g., as indicated by apositioning system). For example, if data from a positioning systemindicates that a user is approaching an environmental hazard (e.g., abody of water or a rapid change in altitude), the eye-gaze threshold canbe initially set to a low value or automatically reduced (e.g., from amanually set value). As an example, assume a manual eye-gaze thresholdis initially set to 20 seconds. If a user then approaches a lake (e.g.,based on analysis of data obtained from a positioning system), theeye-gaze threshold can be automatically reduced to 10 seconds.

In some embodiments, the eye-gaze threshold can depend on a number,speed, and/or trajectory of surrounding vehicles (e.g., indicated by theproximity detector 235 of FIG. 2). For example, assume an eye-gazethreshold is initially manually set to 15 seconds. Further, assume thatbased on the observation of 10 nearby devices, the eye-gaze threshold isautomatically reduced. In this example, if 14 nearby devices aredetected by the device (e.g., a determination is made that the observednumber of nearby devices exceeds the threshold number of 10 devices)having the AR application, the eye-gaze threshold can be automaticallyreduced to 5 seconds. This can be completed to ensure the user's eyesare not fixed on their device while multiple other devices are movingnearby.

As another example, assume that the eye-gaze threshold is dependent onthe speed of nearby devices. Further, assume that if any devicesurpasses 25 mph, a determination can be made that the eye-gazethreshold should to be set to a low value. In this example, if a nearbydevice moving beyond 25 mph is detected, the eye-gaze threshold can beinitially set to a low value (e.g., 3 seconds).

In some embodiments, the eye-gaze threshold can depend on a safetyclassification of a particular location (e.g., based on a safety scoregenerated by the safety profiler 255 of FIG. 2). In these embodiments,the magnitude of the eye-gaze threshold can depend on a safety rating ofa particular location. For example, if a region is classified as“dangerous,” (e.g., based on the location having a low safety score),the eye-gaze threshold can be set to a low value (e.g., 5 seconds). Incontrast, if a region is classified as “safe,” (e.g., based on thelocation having a high safety score), the eye-gaze threshold can be setto a high value (e.g., 20 seconds).

In some embodiments, the eye-gaze threshold is automatically adjustedbased on the movement of the device having the AR application (e.g.,mobile device 200). For example, at a first speed (e.g., stationary) ofthe device, a first eye-gaze threshold can be set (e.g., 20 seconds), ata second speed of the device (e.g., 2 mph), a second eye-gaze thresholdcan be set (e.g., 10 seconds), and at a third speed (e.g., 5 mph) of thedevice, a third eye-gaze threshold can be set (e.g., 5 seconds). Thiscan be implemented such that the user has less time to view theirdisplay without looking up while they are traveling faster (e.g.,running) versus traveling slower (e.g., walking or stationary).

If a determination is made that the eye-gaze threshold is not exceeded,then method 300 returns to operation 305, where additional eye-trackingdata is received. As such, method 300 can loop until an eye-gazethreshold is exceeded.

If a determination is made that the eye-gaze threshold is exceeded, thenan alert is issued. This is illustrated at operation 320. The alert canbe issued to notify the user that they have been viewing their devicebeyond the eye-gaze threshold and they should be aware of theirsurroundings. Alerts can include, but are not limited to, audio, visualand/or haptic feedback.

In some embodiments, the alert can include an audio notification. Theaudio notification can be an alarm having a particular pitch, tone,frequency, and/or amplitude such that the user is quickly notified ofpotential danger. In some embodiments, the audio notification caninclude speech (e.g., “Warning,” “Look Up,” “Danger,” etc.).

In some embodiments, the alert can include visual feedback. The visualfeedback can include displaying text (e.g., “Warning”), symbols (e.g.,“!!!”), images, etc. on the display of the user's device. In someembodiments, a message is transmitted to the user's device. The messagecan indicate that the user has been viewing their screen consecutivelyfor “X” seconds, and the user should look up more often to be aware oftheir surroundings. In some embodiments, the visual feedback issued caninclude automatically transitioning to an outward camera view on theuser's device. This can present the user a view of the real-world andencourage the user to look away from the screen or to view the worldthrough the camera view. This can be implemented to prevent collisionsor missteps on behalf of the user.

In some embodiments, the alert can include haptic feedback (e.g., touchsensory feedback). The haptic feedback can include forces, vibrations,and/or motions exhibited by the device. For example, if a user hasexceeded an eye-gaze threshold, the device can vibrate such that theuser is prompted to be aware of their surroundings.

In embodiments, combinations of alerts can be simultaneously issued. Forexample, combinations of haptic, audio, and visual feedback can besimultaneously issued to the user (e.g., a warning message is displayedon the user's device with a vibration and beep).

Though FIG. 3 only depicts the issuance of alerts in response toeye-gaze threshold breaches, in embodiments, additional actions can becompleted. For example, in some embodiments, the AR application on theuser's device can be temporarily paused or closed in response to abreach of an eye-gaze threshold.

In embodiments, in response to exceeding an eye-gaze threshold, theeye-gaze threshold breach can be associated with the location where thebreach occurred and stored for later use. For example, a safety profiler(e.g., safety profiler 255 of FIG. 2) can consider the amount ofeye-gaze threshold breaches in particular locations when classifyingsaid locations.

The aforementioned operations can be completed in any order and are notlimited to those described. Additionally, some, all, or none of theaforementioned operations can be completed, while still remaining withinthe spirit and scope of the present disclosure.

Referring now to FIG. 4, shown is an example method 400 for enhancingsafety of an AR application (e.g., AR application 130 of FIG. 1 or 220of FIG. 2) by detecting the number, speed, and/or trajectory of nearbydevices, in accordance with embodiments of the present disclosure.

Method 400 initiates at operation 405 where proximity data is received(e.g., by an augmented reality safety overlay (ARSO) of a mobiledevice). The proximity data can indicate the number, speed, and/ortrajectory of nearby devices. As discussed herein, the terms “nearby” or“vicinity” can be defined in any suitable manner. For example, “nearby”and “vicinity” can be defined as any suitable radius around the user'sdevice (e.g., 10 feet, 25 feet, 100 feet, 1 mile, etc.). In someembodiments, the relevant area for safety considerations (e.g., thevicinity) can be based on the technology used to determine the numberand/or type of nearby devices. For example, wireless technologies suchas BLE and Wi-Fi can have relatively short detection ranges, and thusmay lead to a smaller radius for safety considerations. In contrast, GPStechnologies may detect devices from many miles away. Accordingly, thesafety radius for GPS technologies can be larger than that of wirelesstechnologies. However, in embodiments, the safety radius can be defined(e.g., manually) such that the user is alerted of imminent threats.

In embodiments, the proximity data may be received from a satellitepositioning source (e.g., GPS applications such as a map application, asocial networking application, an AR application, etc.) which mayindicate the position of devices within the vicinity of the user'sdevice. The position of these devices can be updated over time and mayallow for the approximation of the speed of the devices.

In some embodiments, the proximity data may be received using wirelesstechnologies such as BLE, Wi-Fi, RFID, UWB, etc. Signals (e.g., thespeed, strength, and/or angle of signals) traveling between transmitters(e.g., a first mobile device) and receivers (e.g., a second mobiledevice) can be used to approximate location. For example, Time ofArrival (TOA), Received Signal Strength Indicator (RSSI), and/or Angleof Arrival (AOA) can be used to approximate the position of a devicecommunicating with the user's device. By measuring the location of thenearby devices with respect to the device having the AR application overtime, the speed and trajectory of nearby devices can be calculated(e.g., by measuring the time period between two measured locations).

The number, speed, and/or trajectory of nearby devices are thendetermined. This is illustrated at operation 410. The number, speed,and/or trajectory of nearby devices are determined based on theproximity data received at operation 405. For example, if, in a givenradius (e.g., 100 feet), a first number of devices (e.g., 15) aredetected with respective speeds (e.g., based on their change in positionover time) at operation 405, the number of devices can be defined as thefirst number (e.g., 15) and the speed of the devices can be defined asthe approximated speed of each respective device. The trajectory ofdevices can be approximated based on the position updates over time.

A determination is then made whether a safety threshold is exceeded.This is illustrated at operation 415. The safety threshold can bedefined to warn the user of the device having the AR application ifconditions surrounding the user appear dangerous (e.g., based on thenumber, speed, and/or trajectory of nearby devices). If a determinationis made that a safety threshold is exceeded, an alert action is issuedto the user's device. This is illustrated at operation 420.

If a determination is made that a safety threshold is not exceeded, thenmethod 400 returns to operation 405, where additional proximity data isreceived. Thus, method 400 may continue looping between operations405-415 until a determination is made that a safety threshold isexceeded.

In embodiments, safety thresholds can be defined in any suitable manner.In some embodiments, safety thresholds are based on the number ofdevices in the vicinity of the user's device. For example, a firstsafety threshold can be defined such that a limit of five devices arepermitted in the vicinity of the user's device. In this example, if sixdevices are observed in the vicinity of the user's device, adetermination is made that the safety threshold is exceeded (and analert action can be issued to the user's device at operation 420). Anynumber of safety thresholds can be implemented. For example, a firstsafety threshold can be defined as five permitted devices, a secondsafety threshold can be defined as ten permitted devices, etc. Thealerts issued at operation 420 can mirror the exceeded safety threshold(e.g., if the first safety threshold is exceeded, the alert can warn theuser that more than five devices are nearby, if the second safetythreshold is exceeded, the alert can warn the user that more than tendevices are nearby, etc.).

In some embodiments, safety thresholds can be based on the speed ofnearby devices. For example, a safety threshold can define a 40 mphlimit for any device in the vicinity of the user's device. In thisexample, if a device moving beyond 40 mph is detected in the vicinity ofthe user's device, a determination can be made that the safety thresholdis exceeded, and an alert action can be issued at operation 420.

In some embodiments, safety thresholds can be based on the trajectory ofnearby devices with respect to the user's device. For example, a safetythreshold can be implemented such that if any device within apredetermined distance (e.g., 20 feet) is likely to cross paths (e.g.,based on a comparison between the user device trajectory and the nearbydevice trajectory) with the user's device, an alert is issued.

In some embodiments, safety thresholds can be based on a combination ofthe number of nearby devices, the speed of nearby devices, and/or thetrajectory of nearby devices. For example, a safety threshold can bedefined such that if ten devices are nearby and at least three of thenearby devices are moving beyond 25 mph, an alert is issued. In thisexample, if 12 devices were detected in the vicinity of the user'sdevice, and only two devices were moving beyond 25 mph, the safetythreshold would not be exceeded. Similarly, if nine devices weredetected in the vicinity of the user's device, and five of the deviceswere moving beyond 25 mph, the safety threshold would also not beexceeded. However, if 12 devices were detected in the vicinity of theuser's device and five of the devices were moving beyond 25 mph, then adetermination would be made that the safety threshold was exceeded, andan alert would be issued at operation 420. The number and/or type ofsafety threshold implemented at operation 415 can vary.

The alerts issued at operation 420 can be the same as, or substantiallysimilar to, the alerts issued at operation 320 of FIG. 3. For example,audio, video, and/or haptic alerts can be issued to the user's devicehaving the AR application. In embodiments, the alerts issued atoperation 420 mirror the conditions of the safety threshold breach atoperation 415. As an example, if a safety threshold triggers if anynearby device exceeds 50 mph, then the alert can include an audiowarning reciting: “Warning, a high speed device is nearby!” Followingthe example above, the alert could further include displaying a warningmessage (e.g., a video alert) reading: “Caution!!! A device movingfaster than 50 mph was detected nearby!”

Though FIG. 4 only depicts the issuance of alerts in response to safetythreshold breaches, in embodiments, additional actions can be completedin response to safety threshold breaches. For example, in someembodiments, the AR application on the user's device can be temporarilypaused or closed in response to a breach of a safety threshold.

Though not shown in FIG. 4, the proximity data captured over time can bestored for later use. For example, a table containing the number, speed,and/or trajectory of nearby devices with corresponding time stamps andlocation tags (e.g., destinations) can be stored and analyzed in thefuture (e.g., by safety profiler 255 of FIG. 2). The number, speed,and/or trajectory of devices at particular time periods and locationscan be used to generate safety scores for regions (at particular timeperiods). Generating safety scores for regions will be further discussedwith reference to FIG. 6.

The aforementioned operations can be completed in any order and are notlimited to those described. Additionally, some, all, or none of theaforementioned operations can be completed, while still remaining withinthe spirit and scope of the present disclosure.

FIG. 5 is a flow diagram illustrating an example method 500 forenhancing the safety of a device (e.g., mobile device 200 of FIG. 2)having an AR application (e.g., AR application 130 of FIG. 1 or 220 ofFIG. 2) using position comparison, in accordance with embodiments of thepresent disclosure.

Method 500 initiates at operation 505, where a user position isreceived. The user position can be received via geographic data of apositioning system (e.g., positioning system 210 of FIG. 2). Forexample, GPS features of the user's device can be used to approximatethe location (e.g., GPS coordinates) of the user's position.

A sought destination position is then received. This is illustrated atoperation 510. The sought destination position can be selected by auser. For example, if the AR application is a mapping application thatguides the user to a physical location (e.g., an address), the soughtdestination can be an address (e.g., or place of interest) which theuser is attempting to reach. As another example, if the AR applicationis a gaming application which allows the user to track virtual objectsor destinations, the sought destination can be a selected virtual objector destination on a virtual map (e.g., with a corresponding physicallocation mapping). Based on the selected sought destination, apositioning system (e.g., GPS) can be configured to determine thecoordinates of the selected destination.

The user position is then compared to the sought destination position.This is illustrated at operation 515. The comparison can output thedistance between the user position and the sought destination. Inembodiments, the distance between the user position and the soughtdestination can be based on the available routes (e.g., roads) betweenthe two points (e.g., the user position and the sought destination). Forexample, in some embodiments, the distance output based on thecomparison calculated at operation 515 can be based on the streets thatcomprise the fastest route between the two points. In some embodiments,however, the distance output based on the comparison can be a linesegment between the two points (e.g., independent of available streetsor paths).

A determination is then made whether a proximity threshold is satisfied.This is illustrated at operation 520. The proximity threshold definesthe distance between the user position and the sought destination atwhich an alert is issued to the user at operation 525. Thus, if adetermination is made that a proximity threshold is satisfied, an alertis issued at operation 525.

If a determination is made that a proximity threshold is not satisfiedat operation 520, then method 500 returns to operation 505, where theuser position is received. Accordingly, method 500 may loop betweenoperations 505 and 520 until a proximity threshold is satisfied.

The proximity threshold can be any suitable distance (e.g., within 100meters, within 50 meters, within 10 meters, upon arrival of the soughtdestination) between the user position and the sought destination atwhich an alert is issued. For example, if a proximity threshold is setsuch that within 10 meters, an alert is issued, if a user is 11 metersfrom the sought destination, the proximity threshold is not satisfied.However, if the user is 7 meters from the sought destination, adetermination is made that the proximity threshold is satisfied.

In embodiments, multiple proximity thresholds can be implemented. Forexample, a first proximity threshold can be defined such that a firstalert is issued if a user is within 100 feet of the sought destination,a second proximity threshold can be defined such that a second alert isissued if the user is within 50 feet of the sought destination, and athird proximity threshold can be defined such that a third alert isissued if the user is within 10 feet of the sought destination.

The alert issued at operation 525 can be the same as, or substantiallysimilar to, the alerts issued at operation 320 of FIG. 3 and operation420 of FIG. 4, respectively. In some embodiments, the intensity (e.g.,the decibels for audio alerts or vibration intensity for haptic alerts)of the alert can depend on the distance between the user position andthe sought destination. For example, assume a proximity threshold is setsuch that an audio alert is triggered if the user position is within 20meters of the sought destination. In this example, upon approaching thesought destination, at 20 meters, the audio alert may be faint (e.g., aquiet alarm). Upon approaching the sought destination, the intensity ofthe audio alert may heighten (e.g., the alarm gets louder whenapproaching the sought destination). Upon reaching the destination theaudio alert may reach a peak intensity. This provides a “hotter” and“colder” approach to reaching the destination, such that the user cantravel the correct direction towards the sought location without needingto look at their device. This can similarly be completed for hapticfeedback. For example, the user's device may initiate with a weakvibration, and upon approaching the sought destination, the vibrationmay intensify. The vibration may then reach a peak intensity just priorto reaching the destination.

The aforementioned operations can be completed in any order and are notlimited to those described. Additionally, some, all, or none of theaforementioned operations can be completed, while still remaining withinthe spirit and scope of the present disclosure.

FIG. 6 is a flow-diagram illustrating an example method 600 forclassifying locations based on historical data (e.g., by safety profiler255), in accordance with embodiments of the present disclosure.

Method 600 initiates where input safety data is received (e.g., bymobile device 200). This is illustrated at operation 605. The inputsafety data can include a number, speed, and/or trajectory of vehiclesindicated in particular locations (e.g., by a plurality of deviceshaving an augmented reality safety overlay) at particular times (e.g.,which may indicate the busyness or danger at particular locations). Inembodiments, the input safety data can include eye-detection thresholdbreaches in particular locations at particular times (e.g., which mayindicate the attentiveness of users in this area). In some embodiments,input safety data can include geographic topology or features based onsatellite technology (e.g., indicating environmental hazards). However,input safety data can be received from any suitable source. For example,in some embodiments, the input safety data can be obtained via theInternet. The input safety data can be obtained from one or more onlinedatabases, blogs, journals, websites, etc.

A location and time period to be classified is identified. This isillustrated at operation 610. In some embodiments, the location and timeperiod to be classified may be selected by a user (e.g., seeking totravel to a particular location). For example, the user can seek to usean AR application at a first location, and select the first location forclassification (e.g., to determine whether the location is safe for ARuse). In some embodiments, locations are classified as data is receivedfor such locations in real-time. Classifications may be updated overtime as new input safety data is received.

The location at the particular time period is then classified based onthe safety data. This is illustrated at operation 615. Theclassification can depend on the type of input safety data received atoperation 605. For example, if only the number and/or speed of devicesare received for a particular location over a particular time period,then the number and/or speed of devices may be the only factorsconsidered when classifying the location. However, in embodiments,multiple safety data inputs can be simultaneously considered whenclassifying a location at a particular time. For example, the number,speed, and/or trajectory of devices, the number of eye-gaze thresholdbreaches, and the environmental hazards in a particular location can allbe simultaneously considered when classifying the location.

In embodiments, the classification can be based on tiers (e.g., HighlyDangerous, Dangerous, Potentially Dangerous, Relatively Safe, and Safe)and/or a numerical scale (e.g., a scale from 0-100 with 0 being the mostdangerous and 100 being the safest). Table 1 depicts an example safetyscore tier table. Table 1 will be referred to in an example discussedbelow.

TABLE 1 Scale Score Dangerous 66-100 Intermediate 33-66  Safe 0-33

Classification can be completed in any suitable manner. In someembodiments, a greater number of devices indicate that a particularregion is more dangerous (e.g., a higher chance of collision). In someembodiments, a greater speed of devices indicate that a particularregion is more dangerous (e.g., as vehicles/bicycles may frequent thislocation). In embodiments, a greater number of environmental hazardsindicate that a particular region is more dangerous. In someembodiments, a greater number of eye-gaze threshold breaches indicatesthat a particular region is more dangerous. In some embodiments, dataobtained from the Internet may indicate the relative safety of a region(e.g., based on a sentiment analysis of the data).

In embodiments, the various factors which may be considered whenclassifying a location may be weighed. For example, the speed of devicesmay account for 50% of the safety classification, the number of devicesmay account for 15% of the safety classification, the number of eye-gazethreshold breaches may account for 15% of the safety classification, andenvironmental hazards may account for 20% of the safety classification.The relative weight of factors considered when classifying a region mayalter based on the number of available sources.

An example safety classification for a location (e.g., a park) at aparticular time period (e.g., 12:00 PM-2:00 PM) is depicted in Table 2below:

TABLE 2 Number of Avg. Avg. Speed Eye-Gaze Environ- Number of of DevicesThreshold mental Devices (mph) Breaches Hazards Total Observed 20 8 3 0Occurrence Safety Limit 40 30 15 1 Weight 0.10 0.50 0.10 0.30 SafetyScore 0.05 0.13 0.02 0.00 0.20 Partition Total Safety 20 Score

As depicted in Table 2, the safety factors for consideration are theaverage number of devices at the location within the time period, theaverage speed of devices at the location within the time period, thenumber of eye-gaze threshold breaches at the location within the timeperiod, and the number of environmental hazards at the location. Theobserved occurrences at the location within the time period are noted inthe second row. In this example, the average number of devices is 20,the average speed of devices is 8 mph, the number of eye-gaze thresholdbreaches is 3, and the number of environmental hazards is 0.

The safety limit (e.g., shown in the 3^(rd) row) defines the magnitudeof occurrences required to reach a maximum danger rating for thatparticular factor. For example, if 40 or more average devices wereobserved, the danger rating for the number of devices would be 1.00(e.g., 100%). As another example, if the average speed of devicesobserved was 15, the danger rating for the average speed of deviceswould be 0.50 (e.g., 50%). As depicted in Table 2, the danger rating forthe average number of devices is 0.50 (e.g., 20/40), the danger ratingfor the average speed of the devices is 0.27 (e.g., 8/30 rounded up),the danger rating for the number of eye-threshold breaches is 0.20(e.g., 3/15) and the danger rating for the number of environmentalhazards is 0.00 (e.g., 0/1).

The weight of each factor limits the impact that each factor has on thefinal safety score. As depicted in Table 2, the average number ofdevices has a weight of 0.10, the average speed of the devices has aweight of 0.50, the number of eye-gaze threshold breaches has a weightof 0.10, and the number of environmental hazards has a weight of 0.30.The danger ratings (e.g., the observed occurrences divided by the safetylimit which cannot exceed 1.00 or 100%) are then multiplied by theweight to receive a safety score partition.

The safety score partition for the average number of devices is 0.05(e.g., 0.50×0.1), the safety score partition for the average speed ofthe devices is 0.13 (e.g., 0.27×0.50 rounded down), the safety scorepartition for the number of eye-gaze threshold breaches is 0.02 (e.g.,0.20×0.10), and the safety score partition for the number ofenvironmental hazards is 0.00 (e.g., 0.00×0.30). The safety scorepartitions are then added to receive the sum of the safety scorepartitions. In this instance, the sum of the safety score partitions is0.20 (e.g., 0.05+0.13+0.02+0.00). The sum of the safety score partitionsis then multiplied by 100 (to scale the value to the reference scaledepicted on Table 1) to attain the total safety score of 20 (e.g.,0.20×100). The total safety score is then referenced against a safetyscore tier table to obtain the classification. In this example, if thetotal safety score from Table 2 is referenced against Table 1, then theclassification is defined as “Safe,” falling between 0-33.

It is noted that this classification technique is merely exemplary.Classification can be completed in any other manner otherwise consistentherein. For example, more or fewer factors may be considered, differentarithmetic operations may be completed to obtain a safety score,different safety classification tiers may be formulated, etc. Themagnitude and range of the safety tier classifications can vary, andthey can be arbitrarily defined.

Once the location and corresponding time period is classified, theclassification is stored. This is illustrated at operation 620. Inembodiments, the classification can be stored in an ARSO (e.g., ARSO 132of FIG. 1 or ARSO 225 of FIG. 2), an AR Application (e.g., ARapplication 130 of FIG. 1 or AR application 220 of FIG. 2), a file, ablock of data, or in any other suitable location.

A determination is made whether the location and corresponding timeperiod are requested (e.g., called). This is illustrated at operation625. If the location and corresponding time period are requested, thenthe classification is transmitted to the requestor. This is illustratedat operation 630. If a determination is made that the location andcorresponding time period are not requested, method 600 returns tooperation 605, where input safety data is received. Thus, method 600 maycontinuously loop between operations 605 and 625 until a location andcorresponding time period are requested.

Following the example above, if a user requests the classification forthe park between 12:00 PM and 2:00 PM, the safety score of “20” may betransmitted to the user with the classification that the location andcorresponding time period is “Safe.” After the classification (e.g., thetier and safety score) is transmitted to the requestor, method 600terminates.

The aforementioned operations can be completed in any order and are notlimited to those described. Additionally, some, all, or none of theaforementioned operations can be completed, while still remaining withinthe spirit and scope of the present disclosure.

Referring now to FIG. 7, shown is a high-level block diagram of anexample computer system 701 (e.g., client devices 102 and 112, server122, and mobile device 200) that may be used in implementing one or moreof the methods, tools, and modules, and any related functions, describedherein (e.g., using one or more processor circuits or computerprocessors of the computer), in accordance with embodiments of thepresent disclosure. In some embodiments, the major components of thecomputer system 701 may comprise one or more CPUs 702, a memorysubsystem 704, a terminal interface 712, a storage interface 714, an I/O(Input/Output) device interface 716, and a network interface 718, all ofwhich may be communicatively coupled, directly or indirectly, forinter-component communication via a memory bus 703, an I/O bus 708, andan I/O bus interface unit 710.

The computer system 701 may contain one or more general-purposeprogrammable central processing units (CPUs) 702A, 702B, 702C, and 702D,herein generically referred to as the CPU 702. In some embodiments, thecomputer system 701 may contain multiple processors typical of arelatively large system; however, in other embodiments the computersystem 701 may alternatively be a single CPU system. Each CPU 702 mayexecute instructions stored in the memory subsystem 704 and may includeone or more levels of on-board cache.

System memory 704 may include computer system readable media in the formof volatile memory, such as random access memory (RAM) 722 or cachememory 724. Computer system 701 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 726 can be provided forreading from and writing to a non-removable, non-volatile magneticmedia, such as a “hard-drive.” Although not shown, a magnetic disk drivefor reading from and writing to a removable, non-volatile magnetic disk(e.g., a “USB thumb drive” or “floppy disk”), or an optical disk drivefor reading from or writing to a removable, non-volatile optical discsuch as a CD-ROM, DVD-ROM or other optical media can be provided. Inaddition, memory 704 can include flash memory, e.g., a flash memorystick drive or a flash drive. Memory devices can be connected to memorybus 703 by one or more data media interfaces. The memory 704 may includeat least one program product having a set (e.g., at least one) ofprogram modules that are configured to carry out the functions ofvarious embodiments.

One or more programs/utilities 728, each having at least one set ofprogram modules 730 may be stored in memory 704. The programs/utilities728 may include a hypervisor (also referred to as a virtual machinemonitor), one or more operating systems, one or more applicationprograms, other program modules, and program data. Each of the operatingsystems, one or more application programs, other program modules, andprogram data or some combination thereof, may include an implementationof a networking environment. Programs/utilities 728 and/or programmodules 730 generally perform the functions or methodologies of variousembodiments.

In some embodiments, the program modules 730 of the computer system 701include an augmented reality safety module. The augmented reality safetymodule may include one or more submodules. For example, the augmentedreality safety module can include an eye-tracking module configured towarn a user if they are viewing a display of their device beyond apredetermined period, a proximity module configured to determine anumber, speed, and/or trajectory of nearby devices and warn a user ifthe conditions indicate a potentially dangerous environment, and aposition comparison module configured to alert a user as they areapproaching a sought destination. The augmented reality safety modulecan further include a classification module configured to classifylocations at particular time periods based on input safety data.

Although the memory bus 703 is shown in FIG. 7 as a single bus structureproviding a direct communication path among the CPUs 702, the memorysubsystem 704, and the I/O bus interface 710, the memory bus 703 may, insome embodiments, include multiple different buses or communicationpaths, which may be arranged in any of various forms, such aspoint-to-point links in hierarchical, star or web configurations,multiple hierarchical buses, parallel and redundant paths, or any otherappropriate type of configuration. Furthermore, while the I/O businterface 710 and the I/O bus 708 are shown as single respective units,the computer system 701 may, in some embodiments, contain multiple I/Obus interface units 710, multiple I/O buses 708, or both. Further, whilemultiple I/O interface units are shown, which separate the I/O bus 708from various communications paths running to the various I/O devices, inother embodiments some or all of the I/O devices may be connecteddirectly to one or more system I/O buses.

In some embodiments, the computer system 701 may be a multi-usermainframe computer system, a single-user system, or a server computer orsimilar device that has little or no direct user interface, but receivesrequests from other computer systems (clients). Further, in someembodiments, the computer system 701 may be implemented as a desktopcomputer, portable computer, laptop or notebook computer, tabletcomputer, pocket computer, telephone, smart phone, network switches orrouters, or any other appropriate type of electronic device.

It is noted that FIG. 7 is intended to depict the representative majorcomponents of an exemplary computer system 701. In some embodiments,however, individual components may have greater or lesser complexitythan as represented in FIG. 7, components other than or in addition tothose shown in FIG. 7 may be present, and the number, type, andconfiguration of such components may vary.

It is to be understood that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather,embodiments of the present disclosure are capable of being implementedin conjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model can includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but can be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported, providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It can be managed by the organization or a third party andcan exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It can be managed by the organizations or a third partyand can exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Referring now to FIG. 8, illustrative cloud computing environment 810 isdepicted. As shown, cloud computing environment 810 includes one or morecloud computing nodes 800 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 800A (e.g., mobile device 200), desktop computer800B (e.g., client devices 102 and 112 and server 122) laptop computer800C (e.g., client devices 102 and 112, server 122, and mobile device200), and/or automobile computer system 800N (e.g., client devices 102and 112, server 122, and mobile device 200) can communicate. Nodes 800can communicate with one another. They can be grouped (not shown)physically or virtually, in one or more networks, such as Private,Community, Public, or Hybrid clouds as described hereinabove, or acombination thereof. This allows cloud computing environment 810 tooffer infrastructure, platforms and/or software as services for which acloud consumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 800A-Nshown in FIG. 8 are intended to be illustrative only and that computingnodes 800 and cloud computing environment 810 can communicate with anytype of computerized device over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring now to FIG. 9, a set of functional abstraction layers providedby cloud computing environment 810 (FIG. 8) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 9 are intended to be illustrative only and embodiments of thedisclosure are not limited thereto. As depicted below, the followinglayers and corresponding functions are provided.

Hardware and software layer 900 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 902;RISC (Reduced Instruction Set Computer) architecture based servers 904;servers 906; blade servers 908; storage devices 910; and networks andnetworking components 912. In some embodiments, software componentsinclude network application server software 914 and database software916.

Virtualization layer 920 provides an abstraction layer from which thefollowing examples of virtual entities can be provided: virtual servers922; virtual storage 924; virtual networks 926, including virtualprivate networks; virtual applications and operating systems 928; andvirtual clients 930.

In one example, management layer 940 can provide the functions describedbelow. Resource provisioning 942 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. For example, resourceprovisioning 942 can allocate additional computing resources to devices(e.g., client devices 102 and 112, server 122, and mobile device 200)which are indicated to have high activity. Metering and Pricing 944provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources can include applicationsoftware licenses. In some embodiments, Metering and Pricing 944indicates the number of allotted licenses to machines in the system.Security provides identity verification for cloud consumers and tasks,as well as protection for data and other resources. User portal 946provides access to the cloud computing environment for consumers andsystem administrators. Service level management 948 provides cloudcomputing resource allocation and management such that required servicelevels are met. Service Level Agreement (SLA) planning and fulfillment950 provide pre-arrangement for, and procurement of, cloud computingresources for which a future requirement is anticipated in accordancewith an SLA.

Workloads layer 960 provides examples of functionality for which thecloud computing environment can be utilized. Examples of workloads andfunctions which can be provided from this layer include: mapping andnavigation 962; proximity detection 964; augmented environmentgeneration 966; eye-tracking 968; transaction processing 970; and dataanalytics processing 972.

As discussed in more detail herein, it is contemplated that some or allof the operations of some of the embodiments of methods described hereinmay be performed in alternative orders or may not be performed at all;furthermore, multiple operations may occur at the same time or as aninternal part of a larger process.

The present disclosure may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent disclosure.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers, and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present disclosure may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present disclosure.

Aspects of the present disclosure are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of thedisclosure. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present disclosure. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the variousembodiments. As used herein, the singular forms “a,” “an,” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. It will be further understood that the terms“includes” and/or “including,” when used in this specification, specifythe presence of the stated features, integers, steps, operations,elements, and/or components, but do not preclude the presence oraddition of one or more other features, integers, steps, operations,elements, components, and/or groups thereof. In the previous detaileddescription of example embodiments of the various embodiments, referencewas made to the accompanying drawings (where like numbers represent likeelements), which form a part hereof, and in which is shown by way ofillustration specific example embodiments in which the variousembodiments may be practiced. These embodiments were described insufficient detail to enable those skilled in the art to practice theembodiments, but other embodiments may be used and logical, mechanical,electrical, and other changes may be made without departing from thescope of the various embodiments. In the previous description, numerousspecific details were set forth to provide a thorough understanding thevarious embodiments. But, the various embodiments may be practicedwithout these specific details. In other instances, well-known circuits,structures, and techniques have not been shown in detail in order not toobscure embodiments.

Different instances of the word “embodiment” as used within thisspecification do not necessarily refer to the same embodiment, but theymay. Any data and data structures illustrated or described herein areexamples only, and in other embodiments, different amounts of data,types of data, fields, numbers and types of fields, field names, numbersand types of rows, records, entries, or organizations of data may beused. In addition, any data may be combined with logic, so that aseparate data structure may not be necessary. The previous detaileddescription is, therefore, not to be taken in a limiting sense.

The descriptions of the various embodiments of the present disclosurehave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

Although the present disclosure has been described in terms of specificembodiments, it is anticipated that alterations and modification thereofwill become apparent to the skilled in the art. Therefore, it isintended that the following claims be interpreted as covering all suchalterations and modifications as fall within the true spirit and scopeof the disclosure.

What is claimed is:
 1. A method comprising: determining, by a processor,an eye-gaze time indicating a period in which a user using an augmentedreality (AR) application is viewing a screen of a mobile device runningthe AR application; comparing, by the processor, the eye-gaze time to aneye-gaze threshold; issuing, in response to a determination that theeye-gaze time exceeds the eye-gaze threshold, an alert to the mobiledevice running the AR application; determining that a number of nearbydevices exceeds a threshold; and reducing, in response to the number ofnearby devices exceeding the threshold, the eye-gaze threshold.
 2. Themethod of claim 1, wherein a front-facing camera of the mobile devicereceives a set of eye-tracking data used to determine the eye-gaze time,wherein the processor determines the eye-gaze time via optical tracking.3. The method of claim 1, further comprising: determining that thenumber of nearby devices falls below the threshold; and increasing, inresponse to the number of nearby devices falling below the threshold,the eye-gaze threshold.
 4. The method of claim 1, further comprising:determining that a speed of a nearby device exceeds a threshold; andreducing, in response to determining that the speed of the nearby deviceexceeds the threshold, the eye-gaze threshold.
 5. The method of claim 1,further comprising: determining that the mobile device is moving at afirst speed; and reducing, in response to determining that the mobiledevice is moving at the first speed, the eye-gaze threshold.
 6. Themethod of claim 5, further comprising: determining that the mobiledevice is moving at a second speed, the second speed being lesser thanthe first speed; and increasing, in response to determining that themobile device is moving at the second speed, the eye-gaze threshold. 7.A system comprising: at least one memory storing program instructions;and at least one processor communicatively coupled to the at least onememory, wherein the processor is configured to execute the programinstructions to perform a method comprising: determining an eye-gazetime indicating a period in which a user using an augmented reality (AR)application is viewing a screen of a mobile device running the ARapplication; comparing, by the processor, the eye-gaze time to aneye-gaze threshold; issuing, in response to a determination that theeye-gaze time exceeds the eye-gaze threshold, an alert to the mobiledevice running the AR application; determining that a speed of a nearbydevice exceeds a threshold; and reducing, in response to determiningthat the speed of the nearby device exceeds the threshold, the eye-gazethreshold.
 8. The system of claim 7, wherein a front-facing camera ofthe mobile device receives a set of eye-tracking data used to determinethe eye-gaze time, wherein the processor determines the eye-gaze timevia optical tracking.
 9. The system of claim 7, wherein the methodperformed by the processor further comprises: determining that a numberof nearby devices exceeds a threshold; and reducing, in response to thenumber of nearby devices exceeding the threshold, the eye-gazethreshold.
 10. The system of claim 9, wherein the method performed bythe processor further comprises: determining that the number of nearbydevices falls below the threshold; and increasing, in response to thenumber of nearby devices falling below the threshold, the eye-gazethreshold.
 11. The system of claim 7, wherein the method performed bythe processor further comprises: determining that the mobile device ismoving at a first speed; and reducing, in response to determining thatthe mobile device is moving at the first speed, the eye-gaze threshold.12. The system of claim 11, wherein the method performed by theprocessor further comprises: determining that the mobile device ismoving at a second speed, the second speed being lesser than the firstspeed; and increasing, in response to determining that the mobile deviceis moving at the second speed, the eye-gaze threshold.
 13. A computerprogram product comprising one or more computer readable storage media,and program instructions collectively stored on the one or more computerreadable storage media, the program instructions comprising instructionsconfigured to cause one or more processors to perform a methodcomprising: determining an eye-gaze time indicating a period in which auser using an augmented reality (AR) application is viewing a screen ofa mobile device running the AR application; comparing, by the processor,the eye-gaze time to an eye-gaze threshold; issuing, in response to adetermination that the eye-gaze time exceeds the eye-gaze threshold, analert to the mobile device running the AR application; determining thatthe mobile device is moving at a first speed; and reducing, in responseto determining that the mobile device is moving at the first speed, theeye-gaze threshold.
 14. The computer program product of claim 13,wherein a front-facing camera of the mobile device receives a set ofeye-tracking data used to determine the eye-gaze time, wherein theprocessor determines the eye-gaze time via optical tracking.
 15. Thecomputer program product of claim 13, wherein the method performed bythe processor further comprises: determining that a number of nearbydevices exceeds a threshold; and reducing, in response to the number ofnearby devices exceeding the threshold, the eye-gaze threshold.
 16. Thecomputer program product of claim 15, wherein the method performed bythe processor further comprises: determining that the number of nearbydevices falls below the threshold; and increasing, in response to thenumber of nearby devices falling below the threshold, the eye-gazethreshold.
 17. The computer program product of claim 13, wherein themethod performed by the processor further comprises determining that aspeed of a nearby device exceeds a threshold; and reducing, in responseto determining that the speed of the nearby device exceeds thethreshold, the eye-gaze threshold.
 18. The computer program product ofclaim 13, wherein the method performed by the processor furthercomprises: determining that the mobile device is moving at a secondspeed, the second speed being lesser than the first speed; andincreasing, in response to determining that the mobile device is movingat the second speed, the eye-gaze threshold.